CLIPS

What is CLIPS?

CLIPS is a productive development and delivery expert system tool which provides a complete environment for the construction of rule and/or object based expert systems. Created in 1985, CLIPS is now widely used throughout the government, industry, and academia. Its key features are:

• Knowledge Representation: CLIPS provides a cohesive tool for handling a wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented and procedural. Rule-based programming allows knowledge to be represented as heuristics, or "rules of thumb," which specify a set of actions to be performed for a given situation. Object-oriented programming allows complex systems to be modeled as modular components (which can be easily reused to model other systems or to create new components). The procedural programming capabilities provided by CLIPS are similar to capabilities found in languages such as C, Java, Ada, and LISP.
• Portability: CLIPS is written in C for portability and speed and has been installed on many different operating systems without code changes. Operating systems on which CLIPS has been tested include Windows XP, MacOS X, and Unix. CLIPS can be ported to any system which has an ANSI compliant C or C++ compiler. CLIPS comes with all source code which can be modified or tailored to meet a user's specific needs.
• Integration/Extensibility: CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, Java, FORTRAN and ADA. CLIPS can be easily extended by a user through the use of several well-defined protocols.
• Interactive Development: The standard version of CLIPS provides an interactive, text oriented development environment, including debugging aids, on-line help, and an integrated editor. Interfaces providing features such as pulldown menus, integrated editors, and multiple windows have been developed for the MacOS, Windows XP, and X Window environments.
• Verification/Validation: CLIPS includes a number of features to support the verification and validation of expert systems including support for modular design and partitioning of a knowledge base, static and dynamic constraint checking of slot values and function arguments, and semantic analysis of rule patterns to determine if inconsistencies could prevent a rule from firing or generate an error.
• Fully Documented: CLIPS comes with extensive documentation including a Reference Manual and a User's Guide.
• Low Cost: CLIPS is maintained as public domain software.

What are Expert Systems?

Conventional programming languages, such as FORTRAN and C, are designed and optimized for the procedural manipulation of data (such as numbers and arrays). Humans, however, often solve complex problems using very abstract, symbolic approaches which are not well suited for implementation in conventional languages. Although abstract information can be modeled in these languages, considerable programming effort is required to transform the information to a format usable with procedural programming paradigms.

One of the results of research in the area of artificial intelligence has been the development of techniques which allow the modeling of information at higher levels of abstraction. These techniques are embodied in languages or tools which allow programs to be built that closely resemble human logic in their implementation and are therefore easier to develop and maintain. These programs, which emulate human expertise in well defined problem domains, are called expert systems. The availability of expert system tools, such as CLIPS, has greatly reduced the effort and cost involved in developing an expert system.

Rule-based programming is one of the most commonly used techniques for developing expert systems. In this programming paradigm, rules are used to represent heuristics, or "rules of thumb," which specify a set of actions to be performed for a given situation. A rule is composed of an if portion and a then portion. The if portion of a rule is a series of patterns which specify the facts (or data) which cause the rule to be applicable. The process of matching facts to patterns is called pattern matching. The expert system tool provides a mechanism, called the inference engine, which automatically matches facts against patterns and determines which rules are applicable. The if portion of a rule can actually be thought of as the whenever portion of a rule since pattern matching always occurs whenever changes are made to facts. The then portion of a rule is the set of actions to be executed when the rule is applicable. The actions of applicable rules are executed when the inference engine is instructed to begin execution. The inference engine selects a rule and then the actions of the selected rule are executed (which may affect the list of applicable rules by adding or removing facts). The inference engine then selects another rule and executes its actions. This process continues until no applicable rules remain.